Alert generation system and method

ABSTRACT

In a processing system a method comprises: receiving measurement data; processing the measurement data to create or update at least two models and one or more characteristics associated with each model based on the measurement data. Each of the models is a representation of a real-world thing. The method further comprises processing the characteristics associated with the models to form one or more new relationships between the models when the characteristics are such that two or more of the models are regarded as being related according to one or more relationship criteria; and processing the relationships to generate one or more alerts when one or more of the relationships meet one or more alert criteria.

This application is a continuation of U.S. application Ser. No.12/736,732, filed on Nov. 4, 2010, which is the U.S. National Phase ofInternational Application No. PCT/AU2009/001266, filed Sep. 24, 2009,which claims the benefit of priority to Australian Application No.2008904973, filed Sep. 24, 2008, each incorporated by reference in itsentirety.

FIELD OF THE INVENTION

The present invention relates to processing measurements to generate analert in certain circumstances.

BACKGROUND

It is useful to monitor objects and events. In many monitoringsituations, most of what is monitored is mundane and does not requireattention. However sometimes events occur that may require attention.Determining when to draw an event to someone's attention is a difficulttask that is not currently handled adequately.

SUMMARY OF THE INVENTION

According to the present invention there is provided in a processingsystem a method comprising:

-   -   receiving measurement data;    -   processing the measurement data to create or update at least two        models and one or more characteristics associated with each        model based on the measurement data, where each of the models is        a representation of a real-world thing;    -   processing the characteristics associated with the models to        form one or more relationships between the models when the        characteristics are such that two or more of the models are        regarded as being related according to one or more relationship        criteria;    -   processing the relationships to generate one or more alerts when        one or more of the relationships meet one or more alert        criteria.

The real-world thing is typically a real-world object, event orphenomenon. In an embodiment, one of the real-world things is an assetand one of the real-world things is an event or phenomenon.

In an embodiment, the or each asset are fix in geographic location andthe events or phenomenon are created when they potentially or actuallypose a threat to the or each asset due to geographical proximity to theone or more of the assets.

In an embodiment, each event or phenomenon model has a delay state thatreduces the relevance of the model over time unless new measurement datais received that relates to the respective model.

In an embodiment, each relationship has a delay state that reduces therelevance of the relationship over time unless a change incharacteristics associated with the respective models between whichthere is the respective relationship is processed.

According to the present invention there is provided in a processingsystem a method comprising:

-   -   receiving measurement data, wherein the measurement data is        obtained by measuring at least two real-world things;    -   processing the measurement data to create at least two models,        each model representing one of the measured at least two real        world things;    -   processing the measurement data to create characteristics        associated with each model based on the measurement data,        wherein the characteristics describe the respective real-word        thing and/or its behaviour as measured;    -   receiving updated measurement data, wherein the updated        measurement data is obtained by a later measurement of the at        least two real-world things; processing the updated measurement        data to update each of the at least two models and to update the        one or more characteristics associated with each model based on        the updated measurement data;    -   providing one or more relationship criteria for testing whether        two models are to be regarded as related according to the type        of thing that the real-world things are representing;    -   processing the characteristics associated with the models by        testing whether the relationship criteria are met, and in the        event that the relationship criteria are met forming one or more        relationships between the models that meet the relationship        criteria;    -   processing the characteristics associated with the models to        form characteristics associated with formed relationships        between models; processing the updated characteristics        associated with the models to update the characteristics        associated with the relationships;    -   providing one or more alert criteria for testing whether a        relationship between models requires alerting;

processing the characteristics associated with the relationships bytesting whether the alert criteria are met, and in the event that thealert criteria are met generating one or more alerts.

The real-world thing is typically a real-world object, event orphenomenon. In an embodiment one of the real-world things is an assetand one of the real-world things is an event or phenomenon.

According to the present invention there is provided in a methodcomprising:

-   -   categorising received measurement data as related to one or more        models and storing the categorised data in association with the        related one or more models in a storage device, wherein each of        the one or more models is a representation of a real-world        thing, wherein one or more of the models have one or more        associated characteristics that are based on the related        measurement data;    -   forming one or more relationships between the models when the        characteristics are such that two or more of the models are        regarded as related according to one or more relationship        criteria and storing the formed relationships in association        with the related two or more models in the or another storage        device;    -   generating one or more alert signals when one or more of the        relationships meet one or more alert criteria.

The measurement data typically originates from one or more instrumentsor sensors and typically comprises a measurement from the sensor,information about the sensor (such as an identifier of the sensor) and atime that the measurement was taken. A measurement may be an observationtaken at a particular location.

The models may have other associated characteristics based ondefinitional data of the modelled real-world thing. The definitionaldata may be metadata related to the measurement data.

The relationship criteria typically comprise rules which define when twoor more models are related according to the respective modelcharacteristics.

In an embodiment one or more of the relationships have one or moreproperties that are based on the model characteristics or themeasurement data related to the model in the respective relationship.Generating the one or more alerts occurs when one or more of therelationship properties meet one or more of the alert criteria.

The alert criteria typically comprise rules which define when one of therelationships is significant according to the respective relationshipproperties.

In an embodiment one or more of the characteristics comprise a currentstate of the real-world thing. Typically the current state of thereal-world thing is derived or inferred from measurement data related tothe respective models. In some embodiments the current state is acomponent of the measurement data.

In an embodiment each model has one or more associated states, eachstate is updated when there is change in the measurement data related tothe respective model. Updating a state of a model may change the stateor leave it unchanged. An associated state of a model may be updatedwhen there is a change in another model characteristic or in arelationship property or when an alert is generated.

In an embodiment one or more of the relationship properties comprise acurrent state of the relationship between one real-world thing andanother real-world thing. Typically the current state of therelationship is derived or inferred from measurement data related to therespective models that have the respective relationship and/orcharacteristics of the respective models.

In an embodiment each relationship has one or more associated states,each state is updated when there is change in one or more of therespective models that form the relationship. Updating the state of arelationship may change the state or leave it unchanged. An associatedstate of a relationship may be updated when there is a change in a modelcharacteristic or in another relationship property or when an alert isgenerated.

In an embodiment at least a portion of the measurement data has ageographic or geo-spatial significance of the real-world thing.

In an embodiment one of the characteristics associated with each modelis a geographic location of the real-world thing represented by themodel.

In an embodiment one of the characteristics associated with each modelis a geographic extent of the real-world thing represented by the model.

In an embodiment one of the characteristics associated with each modelis a time at which one or more of the other characteristics are valid.For example, the time may be when a measurement is taken, such that themeasurement is valid as at that time, but the measurement might not bevalid later because circumstances may have changed.

In an embodiment, generation of the alert triggers sending anotification to an actor. In an embodiment a notification is sent to anactor when one or more alerts are generated and notification criteriaare met. In an embodiment the actor is a person, alternatively the actormay be a computer system. In an embodiment a notification may only betriggered when a plurality of alerts are generated.

Sometimes a new model will need to be created when new measurement datais received. In an embodiment the method further comprises creating anew model in the event that the received measurement data meet triggercriteria for creation of a model representing a real-world thing.

In an embodiment, processing the measurement data to be categorised asbeing related to one or more models comprises creating a new model inthe event that a model related to the measurement data does not exist.

In an embodiment the method further comprises assigning characteristicsto the new model based on the measurement data. In an embodiment the newmodel is selected from a plurality of predetermined model typesaccording to the measurement data.

In an embodiment, processing the measurement data to be categorised asbeing related to one or more models comprises identifying which of aplurality of existing models the measurement data relates to. In anembodiment the method further comprises updating one or morecharacteristics related to the or each identified model based on themeasurement data. In an embodiment updating one or more characteristicscomprises updating the one or more characteristics only when there is achange in the measurement data related to the respective identifiedmodel.

In an embodiment the method further comprises terminating a model in theevent that the measurement data indicates that the real-world thing thatthe model represents is no longer measured or the real-world thing nolonger exists.

In an embodiment a graphical representation of one or more of the modelsis displayed. In an embodiment a graphical representation of one or moreof the relationships is displayed.

Sometimes a new model will need to be created when characteristics ofone or more other models require a composite or derivative model. In anembodiment the method further comprises creating a new model in theevent that the model characteristics meet one or more model creationcriteria for creation of a new model representing a real-world thing.

In an embodiment the method further comprises creating a new model inthe event that the characteristics meet one or more model creationcriteria and a model of the real-world thing does not exist.

In an embodiment the method further comprises assigning newcharacteristics to the new model based on the characteristics of the oneor more models that caused the creation of the new model. In anembodiment the new model is selected from a plurality of predeterminedmodel types according to the characteristics of the one or more modelsthat caused the creation of the new model. In an embodiment the one ormore of the model creation criteria are met when the characteristics ofexisting models change to a state such that the new model should becreated. In one example two existing models may be combined into the newmodel.

The model creation criteria allow for models to be created based oninferences, interpolations, or derivations of characteristics of othermodels.

Characteristics of one model may update the characteristics of anothermodel. In an embodiment the method further comprises identifying whichof a plurality of existing models the characteristics of one or moreother models relate to when the characteristics of the one or more othermodels meet one or more model update criteria. In an embodiment themethod further comprises updating one or more characteristics related tothe or each identified model based on the characteristics of the one ormore other models. In an embodiment updating one or more characteristicscomprises updating the one or more characteristics only when there is achange in the characteristics of the one or more other models. The modelupdate criteria may be the same as the model creation criteria, in thata new model may be created and an existing model updated when thecriteria are met.

The model update criteria allow for models to be updated based oninferences, interpolations, or derivations of characteristics of othermodels.

Certain relationships may trigger the creation of new models. In anembodiment the method further comprises creating a new model in theevent that the relationship properties meet one or more other modelcreation criteria and a model related to the real-world thingsrepresented by the models does not exist. In an embodiment the methodfurther comprises assigning characteristics to the new model based onthe relationship properties. In an embodiment the new model is selectedfrom a plurality of predetermined model types according to therelationship properties.

The other model creation criteria allow for models to be created basedon inferences, interpolations, or derivations of properties ofrelationships between other models.

In an embodiment the method further comprises identifying which of aplurality of existing models the relationships relate to when therelationship properties meet one or more other model update criteria. Inan embodiment the method further comprises updating one or morecharacteristics related to the or each identified model based on therelationship properties. In an embodiment updating one or morecharacteristics comprises updating the one or more characteristics onlywhen there is a change in the relationship properties related to therespective identified model. The other model creation criteria may bethe same as the other model update criteria, in that a new model may becreated and an existing model updated when the other criteria are met.

The other model update criteria allow for models to be updated based oninferences, interpolations, or derivations of properties ofrelationships between other models.

In an embodiment one or more characteristics of each model is alteredwith time. In an embodiment the alteration is a change of a first stateto a second state in the event that the respective characteristic is notupdated within a time period. In an embodiment the second state is anindication of the model expiring, such that the model is no longer validand may be deleted.

In an embodiment one or more relationship properties is altered withtime. In an embodiment the alteration is a change of a first type ofrelationship property to a second type of relationship property in theevent that the respective relationship is not updated with a timeperiod. In an embodiment the second type of relationship is anindication of the relationship expiring, such that the relationship isno longer valid and may be deleted.

In an embodiment the notification comprises a message to the actor,wherein the message comprises information derived from one or more of:the relationship properties related to a model which caused the one ormore alerts, the characteristics of the models in the relationship whichcaused the alert, or the measurement data on which the characteristicsare based that were used to form the relationship which caused the oneor more alerts.

In an embodiment updating of the model characteristics is event drivenaccording to updates to the measurement data.

In an embodiment updating of the relationship properties is event drivenaccording to updates to the model characteristics.

Also according to the present invention there is provided a systemcomprising:

-   -   an input for receiving measurement data;    -   a model processor for creating one or more models based on the        received measurements data and for maintaining one or more        characteristics of the models based on the measurement data,        wherein each of the one or more models is a representation of a        real-world thing;    -   a relationship processor for forming one or more relationships        between the models when one or more of the characteristics are        such that two or more of the models are regarded as being        related according to one or more relationship criteria;    -   an alert processor for generating one or more alerts when one or        more of the relationships meet one or more alert criteria.

In an embodiment the system further comprises a received data processorfor categorising the measurement data as being related to one or moremodels.

In an embodiment the system further comprises a memory for maintaining arecord of the one or more characteristics and properties of the one ormore relationships.

In an embodiment the model processor is configured to operate as one ormore state machines, each state machine tracking the current state of arespective model.

In an embodiment the relationship processor is configured to operate asone or more state machines, each state machine tracking the currentstate of respective relationships between models.

In an embodiment the system further comprises a graphics engine forcausing a graphical representation of one or more of the models to bedisplayed.

In an embodiment the system further comprises a graphics engine forcausing a graphical representation of one or more of the relationshipsto be displayed.

In an embodiment the model processor comprises one or more modules, eachmodule for creating and maintaining one or more of the models based onthe received measurement data.

In an embodiment the relationship processor comprises one or moremodules, each module for forming and maintaining one or more of therelationships based on the models.

In an embodiment the system further comprises a notifier for notifyingan actor when an alert is generated.

In an embodiment the system further comprises a message constructor forproviding the actor with a message as part of the notification.

In an embodiment the message constructor is configured to construct themessage from one or more of: the relationships related to a model whichcaused the alert, the characteristics of the models in the relationshipwhich caused the alert, or the measurement data on which thecharacteristics are based that were used to form the relationship whichcaused the alert.

In an embodiment the system further comprises an event processor forcontrolling the modules and transferring event messages to and betweenmodules.

In an embodiment the system further comprises an event logger forlogging the creation of models, updating of models, the creation orupdating of relationships between models or the generation of an alert.

In an embodiment the system further comprises a report manager forpreparing and delivering a report on events logged by the event logger.

According to the present invention there is provided a methodcomprising:

-   -   receiving measurement data;    -   processing the measurement data to be categorised as being        related to one or more models of a real-world thing, wherein the        one or more related models are associated with a geographical        characteristic based on the measurement data, wherein each        geographic characteristic comprises an area or volume of        relevance and a geographic location of the area or volume or        relevance;    -   processing the geographical characteristics associated with the        models to determine whether any of the areas or volumes of        relevance intersect or are within a specified proximity;    -   generating an alert when there is an intersection or the volumes        of relevance are determined to be within the proximity.

In an embodiment one or more of the models relate to an object having afixed geographic location.

In an embodiment one or more of the models relate to an object having avariable geographic location.

In an embodiment one or more of the models relate to an event that mayoccur at a fixed geographic location.

In an embodiment one or more of the models relate to an event that mayoccur at a variable geographic location.

In an embodiment one or more of the models relate to a phenomenon thatmay occur in geographic area.

In an embodiment one or more of the models relate to an object, event orphenomenon that is transient or is movable.

In an embodiment the method further comprises processing thegeographical characteristics associated with the models to determinewhether they are likely to intersect and generating an alert when thereis a likelihood of an intersection.

In an embodiment the method further comprises sending a notification ofthe alert.

In an embodiment the method further comprises applying filtering to thealert such that the alert is only maintained in predetermined conditionsand sending a notification of the alert when the alert is maintained.

In an embodiment processing the measurement data occurs periodically.

In an embodiment the period between processing the measurement data isadjustable.

In an embodiment processing the geographical characteristics associatedwith the models to determine whether they intersect occurs periodically.

In an embodiment the period between each determination of whether thereis an intersection is adjustable.

In an embodiment the one or more models are associated with othercharacteristics based on the measurement data.

In an embodiment the other characteristics are used to determine one ormore of the following:

-   -   the period between processing the measurement data;    -   the period between each determination of whether there is an        intersection;    -   the nature of the filtering applied to the alert.

In an embodiment at least one of the models is a representation of atangible asset.

In an embodiment one of the models is a representation of an object,event or phenomenon that is a threat to a tangible asset.

In an embodiment the area or volume of relevance is determined byextrapolating an area or volume that may be relevant to the model.

According to the present invention there is provided a systemcomprising:

-   -   a receiver of measurement data;    -   a processor for processing the measurement data to be        categorised as being related to one or more models of a        real-world object, event or phenomenon, wherein the one or more        related models are associated with a geographical characteristic        based on the measurement data, wherein each geographical        characteristic comprises an area or volume of relevance and a        geographic location of the area or volume or relevance;    -   a processor for processing the geographical characteristics        associated with the models to determine whether any of the areas        or volumes of relevance intersect or are within a specified        proximity;    -   a processor for generating an alert when there is an        intersection or the volumes of relevance are determined to be        within the proximity.

According to the present invention there is provided a systemcomprising: an object creator which triggers creation of a plurality ofobjects, each object being created when input data meets object creationcriteria, wherein the objects are at least two models of real-worldthings, at least one relationship between the models and an alertgenerator;

a processor module for each of the created objects, each processormodule receives data, processes the data including applying criteria tothe received data, and stores the processed data;

wherein when the created object is a model object, the received data ismeasurement data, the criteria is one or more rules that reflect thatthe measurement data is relevant to a characteristic of the real-worldthing represented by the model and the stored data is characteristics ofthe model based on the measurement data;

wherein when the created object is a relationship object, the receiveddata is the model characteristics, the criteria is one or more rulesthat reflect that the real-world thing of one model has an influenceover, relevance to or is related to the real-world thing of anothermodel and the stored data is relationship properties based on therelevant model characteristics,

wherein when the created object is a relationship object, the receiveddata is the relationship properties, the criteria is one or more rulesthat reflect the relationship between the modelled real world things issignificant and the stored data is an alert based on the relationshipproperties.

In an embodiment the system further comprises a notifier configured tonotify an actor of one or more alerts when the alerts meet anotification criterion.

According to the present invention there is provided a methodcomprising: triggering creation of a plurality of objects, each objectcreated when input data meets object creation criteria, wherein theobjects are at least two models of real-world things, at least onerelationship between the models and an alert generator;

for each of the created objects, receiving data, processing the dataincluding applying criteria to the received data, and storing theprocessed data;

wherein when the created object is a model object, the received data ismeasurement data, the criteria is one or more rules that reflect thatthe measurement data is relevant to a characteristic of the real-worldthing represented by the model and the stored data is characteristics ofthe model based on the measurement data;

wherein when the created object is a relationship object, the receiveddata is the model characteristics, the criteria is one or more rulesthat reflect that the real-world thing of one model has an influenceover, relevance to or is related to the real-world thing of anothermodel and the stored data is relationship properties based on therelevant model characteristics,

wherein when the created model is an alert generator object, thereceived data is the relationship properties, the criteria is one ormore rules that reflect the relationship between the modelled real worldthings is significant and the stored data is an alert signal based onthe relationship properties.

In an embodiment the method further comprises notifying an actor of oneor more alerts when the alerts met a notification criterion.

According to the present invention there is a system comprising:

-   -   means for receiving measurement data;    -   means for processing the measurement data to create or update at        least two models and one or more characteristics associated with        each model based on the measurement data, where each of the        models is a representation of a real-world thing;    -   means for processing the characteristics associated with the        models to form one or more relationships between the models when        the characteristics are such that two or more of the models are        regarded as being related according to one or more relationship        criteria;    -   means for processing the relationships to generate one or more        alerts when one or more of the relationships meet one or more        alert criteria.

According to the present invention there is a system comprising:

-   -   means for categorising the received measurement data as related        to one or more models, wherein each of the one or more models is        a representation of a real-world thing, wherein one or more of        the models have one or more associated characteristics that are        based on the related measurement data;    -   means for forming one or more relationships between the models        when the characteristics are such that two or more of the models        are regarded as related according to one or more relationship        criteria;    -   means for generating one or more alerts when one or more of the        relationships meet one or more alert criteria.

According to the present invention there is a system comprising:

-   -   receiving measurement data;    -   means for processing the measurement data to be categorised as        being related to one or more models of a real-world thing,        wherein the one or more related models are associated with a        geographical characteristic based on the measurement data,        wherein each geographic characteristic comprises an area or        volume of relevance and a geographic location of the area or        volume or relevance;    -   means for processing the geographical characteristics associated        with the models to determine whether any of the areas or volumes        of relevance intersect or are within a specified proximity;    -   means for generating an alert when there is an intersection or        are determined to be within the proximity.

According to the present invention there is a system comprising: meansfor triggering creation of an object when input data meets objectcreation criteria, wherein the objects are at least two models of areal-world things, at least one relationship between the models and analert generator;

for each of the created objects, means for receiving data, processingthe data including applying criteria to the received data, and storingthe processed data; wherein the received data of the model objects aremeasurement data, the criteria is one or more rules that reflect thatthe measurement data is relevant to a characteristic of the real-worldthing represented by the model and the stored data is characteristics ofthe model based on the measurement data;

wherein the received data of the relationship object is the modelcharacteristics, the criteria is one or more rules that reflect that thereal-world thing of one model has an influence over, relevance to or isrelated to the real-world thing of another model and the stored data isrelationship properties based on the relevant model characteristics,wherein the received data of the alert generator object is therelationship properties, the criteria is one or more rules that reflectthe relationship between the modelled real world things is significantand the stored data is an alert based on the relationship properties.

According to the present invention there is provided a computer programembodied in the form of a computer readable medium comprisinginstructions, which when executed control a computer to:

-   -   perform one of the methods described above.

According to the present invention there is provided a computer programembodied in the form of a computer readable medium comprisinginstructions, which when executed control a computer to:

-   -   operate as one of the systems described above.

DESCRIPTION OF ACCOMPANYING DRAWINGS

In order to provide a better understanding example embodiments of thepresent invention will now described, by way of example only, withreference to the accompanying drawings, in which:

FIG. 1 is a schematic diagram of a method according to an embodiment ofthe invention;

FIG. 2 is a schematic diagram of a system according to an embodiment ofthe invention;

FIG. 3 is a schematic diagram of a first portion of a system accordingto another embodiment of the invention;

FIG. 4 is a schematic diagram of a second portion of the systemaccording to embodiment of FIG. 3;

FIG. 5 is a schematic diagram of the third portion of the systemaccording embodiment of FIG. 3;

FIG. 6 is a schematic block diagram of a system architecture, accordingto an embodiment of the invention;

FIG. 7 is a schematic block diagram of a solution architecture accordingto an embodiment of invention;

FIG. 8 is a schematic block diagram showing an engine portion of thesolution architecture of FIG. 7;

FIG. 9 is a state diagram example used in the architecture of FIG. 7;

FIG. 10 is another state diagram example used in the architecture ofFIG. 7;

FIG. 11 is an example screenshot of a graphical user interface producedusing architecture of FIG. 7;

FIG. 12 is a schematic block diagram of another architecture accordingto an embodiment of invention;

FIG. 13 is a schematic block diagram showing an engine portion of thesolution architecture FIG. 12;

FIG. 14 is a state diagram example used in the architecture of FIG. 12;

FIG. 15 is an example screenshot of a graphical user interface producedusing the architecture of FIG. 12;

FIG. 16 is another example screenshot of a graphical user interfaceproduced using architecture of FIG. 12;

FIG. 17 is a schematic diagram of system according to an embodiment ofinvention;

FIG. 18 is a diagram of a fire threat monitoring system according to anembodiment of the invention; and

FIG. 19 is a diagram of a lightning monitoring system according to anembodiment of the invention.

DESCRIPTION OF EXAMPLE EMBODIMENTS

Referring to FIG. 1 there is shown a processing method 10. The method 10comprises receiving 16 measurement data items 14. Each data item 14 isgenerated by one or more data sources 12. The received data items 14 areprocessed 24 to form or update a plurality of models 28. Each model 28represents a real-world thing or an aspect of the real-world thing. Thereal-world thing will typically be an object, event or phenomenon. Eachmodel 28 has one or more characteristics which are directly orindirectly a reflection of the real-world thing based on the data items14.

The characteristics are processed 32 to produce relationships 34 betweenthe models 28. The relationships 34 have properties based on thecharacteristics 30. The properties of the relationships 34 are processed38 to generate alerts 40.

Each data item 14 may include a measurement of one or more real-worldthings. Each data item 14 will typically comprise a measured value, atime/date at which the measurement was taken and an identification ofthe source of the data item 14 so that it can be related to therespective real-world thing. The data items 14 may comprise otherinformation as well. Typically each data item 14 will be transmittedfrom an instrument, sensor or another system or device that measures orrecords a measurable feature of the respective real-world thing. Eachdata item 14 may be a discreet data record, a collection of records or adata stream.

Examples of real-world things are: people, vehicles (land-craft),aircraft, power-lines, railway lines, buildings, devices, machinery,forests, bush-land, property, dams, mining or industrial processes, bushor forest fires, lightning strikes, floods, weather, storms, tsunamis,storm surges, tides, water level, volcanoes or natural disasters. Thislist is intended to be indicative and not exhaustive.

Examples of measurement data 14 created by an instrument are forexample: a speed, direction, departure location, current location,destination or activity, a fixed asset location or geographic extent,time, date, season, temperature, predicted temperature, fire, flood orstorm etc location, extent, severity, intensity, predicted path,area/volume of effect, seismometer readings, or an authority issuedwarning. This list is intended to be indicative and not exhaustive.

The measurement data 14 is typically transmitted over a transmissionmedium 18, such as a computer network that may be for example, theInternet. Alternatively, the transmission medium 18 may be a local areanetwork, a wide area network or some other suitable transmission medium.The transmission medium 18 may comprise one or more data transmissionchannels 20. For example, when the data item 14 is generated by aninstrument, the instrument may be connected via the Internet to agateway 22, with the transmission path over the Internet being aparticular data transmission channel 20. The measurement data 14 isreceived 16 and collected at one or more gateways 22. Each gateway 22can receive pushed measurement data 12 or actively pulls or harvests themeasurement data 14. Each gateway 22 will typically have one or moredata transmission channels 20 associated with it, such that only thosedata transmission channels 20 associated with each gateway 22 willprovide the respective gateway 22 with the measurement data 14. Eachdata transmission channel 20 will typically have one or more sources 12of the measurement data 14 associated with it, such that only thosesources 12 of the measurement data associated with the respective datatransmission channel 20 will provide the data transmission channel 20with the respective measurement data 14.

The collected measurement data 14 is provided 26 to one or more modelprocessors (described further below). The one or more model processorsform and update 24 the one or more models 28 according to the relevantmeasurement data 14. One or more relationship processors (describedfurther below) obtain messages 30 comprising characteristics of themodels 28 to form the relationships 34. Each relationship 34 is formedby the relationship processors analysing the characteristics from one ormore models 28. One or more alert processors (described further below)obtain messages 36 comprising properties of each relationship 32 togenerate 38 alerts 40 by analysis of the relationship properties. Eachalert 40 generated is analysed 44 to determine whether to provide anotification 46 to an actor via a delivery system. The actor may be asystem or a person. The system or person is then able to review 48 thenotification 46 in order to instigate an appropriate action 50. Thenotification 46 may result from or notify about one or more alerts 40.

Referring to FIG. 2, there is shown a processing system 101 whichcomprises one or more measured data sources 100, which collectivelyproduce the measurement data 14 (of FIG. 1). The data sources 100 areconnected 102 to a model processor 104. The model processor 104 createsthe models 24. The model processor 104 may provide a processing modulefor each model 24. Model processor 104 stores the models 24 andcharacteristics of models 24 in a model store 106. The model processor104 has a checking element 108 for checking whether a newly createdmodel or a model update needs to be presented in a live environment,such as a web site. Those models or model characteristics that are to beincluded in the live environment are collected by collector 126.

The models 26 and characteristics of the models are provided by messageover connection 110 to relationship processor 112. Alternatively modelprocessor 104 sends a signal that there is a change in the models 24,that is, a new model has been created or an update to a model hasoccurred. Relationship processor 112 analyses the models 24 and theircharacteristics to determine whether a relationship exists between themodels which is a reflection of a relationship between the real-lifethings. When a relationship is found to exist, a representation 34 ofthe relationship between the models and its properties is stored in arelationship store 114. The relationship processor 112 has a checkingelement 116 that checks whether any changes to the relationshipproperties should be presented in the live environment. Thoserelationships that are to be presented in the live environment arecollected by collector 126.

The generated relationships 34 are sent by message 118 to an alertprocessor 120 which analyses the relationships 34 and creates alerts 40based on the relationship properties. The alert 40 may triggergeneration of a notification 46 to the actor by the notification messageconstructor 124. The notification 46 is stored in a notification store122. The notification 46 is sent over a transmission medium 128 to oneor more notifiers which inform the actor. In one embodiment the notifieris the live environment in the form of a Graphical User Interface (GUI)130, which may be in the form of the web browser. In another embodimentthe notifier is a third party application 132. In another embodiment thenotifier is a message system 134 which sends a message, such as bye-mail or text message to a portable device.

More complex implementations of the method and system may providefeedback from model to model, relationship to relationship, relationshipto model, alert to model or alert to relationship.

Referring to FIGS. 3-5, a more detailed embodiment of the system 101 ofFIG. 2 is described. The measurement data 14 is typically in the form ofdata records or a data stream when produced by the data sources 100.Each data source 150 may have a respective source gateway 154. Thesource gateways 154 may be implemented as a pre-processor 152. Thepre-processor 152 performs pre-processing which may comprise receivingthe data records/data stream and formatting the data into a standardform. In an event driven embodiment the generation of a standardiseddata record will raise a data arrived event flag. Alternatively a dataarrived event message is sent to the model processor 104.

Each standardised data record is provided over connection 102 to themodel processor 104. Alternatively when the data arrives an event flagis raised, or the data arrived event message is received, the modelprocessor 104 will fetch the standardised data record from a buffer orqueue. Model processor 104 accesses a source data assessment rule-base156 to determine whether the data has relevant information to a model.When the data is relevant to a model a checking element 158 of the modelprocessor 104 determines whether the model that the data is relevant toalready exists. When the model does not exist 164 a model 28 of acertain type is created by model creation element 166 of the modelprocessor 104. Each model may have the following characteristics, forexample: an identification, a model type, a current state, criteria forchanging the state, a methodology for creation and termination, otherinformation—such as a geographic location. The characteristics arestored in the model store 106 for access by the model processor 104 andthe relationship processor 112. The model processor 104 can operate astate machine to track the current state of the model according to thecriteria for changing the state. The state machine may simply transitionor track states with a trivial implementation, or the state machine maybe implemented as a state machine processor, depending on therequirements of the application. The current state is usually one of thecharacteristics of the model.

When the model 28 already exists 160 characteristics of the model 28 areupdated. For example the data may trigger the state machine to changethe state of the model according to a rule of the criteria for changingthe state. The creation or update to the model 28 is recorded in themodel store 106.

In some embodiments the model processor 104 accesses a model decayrule-base 168, which determines the way in which a model (or usually thestate of the model) is subjected to decay over time so that the model(or its current state) becomes less relevant with time unless it isupdated by the arrival of new data.

The model processor 104 may query and extract information from the modelstore 106 using query element 172. Some models may be created based onthe characteristics of other models. The model processor 104 may queryand access via connection 178 the relationship store 114. The modelprocessor 104 may use this information when applying the rule-base 156to decide whether data is relevant to a model. In this case the modelthat is created may be composite or it may be a representation of avirtual thing rather that a real-world thing. Such models may be onlypartly directly based or may be indirectly based on the measurementdata.

Model broadcasting rule base 176 is used by checking element 108 todecide whether a model (or characteristics thereof) is provided to thelife environment.

In an event driven embodiment the creation or updating of a model willraise a models changed event flag. Alternatively a models changed eventmessage is sent to the relationship processor 112.

Each created model or updated model is provided over connection 110 tothe relationship processor 112. Alternatively when the models changedevent flag is raised or the models changed event message is received,the relationship processor 112 will fetch the characteristics of thecreated/updated model from the model store 106 via connection 174.Relationship processor 112 accesses a model relationship rule-base 200to determine whether two or more models have a relationship. When arelationship is determined to exist a checking element 202 of therelationship processor 112 determines whether a record of therelationship already exists. When a record of the relationship does notexist 208, a record of properties of the relationship 34 of a certaintype is created by relationship record creation element 210 of therelationship processor 112. Each relationship record may for examplehave the following properties: an identification, a relationship type, acurrent state, criteria for changing the state, a methodology forcreation and termination, references to the model in the relationship,other information. The relationship processor 112 will typically operatea state machine to track the current state of the relationship accordingto the criteria for changing the state. The current state is typicallyone of the relationship properties stored in the relationship store 114.

When the relationship record 34 already exists 204, properties of therelationship 34 are updated. For example, a change in a model maytrigger the state machine to change the state of the relationship thatthe model has with another model according to a rule of the criteria forchanging the state. The creation or update to the relationship 34 isrecorded in the relationship store 114.

In some embodiments the relationship processor 112 accesses arelationship decay rule base 212, which determines the way in which arelationship (or usually the state of the relationship) is subjected todecay over time so that the relationship (or its current state) becomesless relevant with time, unless it is updated by a new model or changein a model causes a change in the relationship.

The relationship processor 112 may query and extract information fromthe relationship store 114 or the model store 106 via connection 174using query element 216. The relationship processor 112 may query andaccess via connection 222 the notification store 122. The relationshipprocessor 112 may use this information when applying the rule-base 200to decide whether models have a relationship. In this case therelationship that is created may be composite. Such models may be onlypartly directly based or indirectly based on the measurement data.

Relationship broadcasting rule base 220 is used to decide whether arelationship (or property thereof) is provided to the life environmentby checking element 116.

In an event driven embodiment the creation or updating of a relationshipwill raise a relationships changed event flag. Alternatively arelationships changed event message is sent to the alert processor 120.

Each created relationship or updated relationship 34 is provided overconnection 118 to the alert processor 120. Alternatively when therelationships changed event flag is raised, or the relationships changedevent message is received, the alert processor 120 will fetch theproperties of the created/updated relationship from the relationshipstore 114 via connection 218. Alert processor 120 accesses arelationship notification rule-base 250 to determine whether therelationship should generate an alert 40 and/or a notification 46. Insome embodiments the alert processor sends the alert as thenotification. In other embodiments a notification processor decides whenand how to send a notification based on the alerts.

When a relationship is determined to exist a checking element 252 of thealert processor 120 determines whether to generate a notification 46,such as whenever a new relationship is formed. When the relationship isnew 254 a recording of the notification 46 of a certain type is createdby relationship record creation element 256 of the alert processor 118.Also when the notification is to be send 254′ this causes a notificationmessage constructor 124 to create a notification 46. Each notification46 may have the following information for example: an identification, anotification type, reason for generation of the notification, such asthe models in the relationship that cause the notification and the typeand/or current state of the relationship, other information.

When the notification 46 is not new 260, a re-issue element 262determines if another notification 46 should be sent, for example there-issue element may operate a re-warn period during which anothernotification is not send until the period expires.

The creation or update to the alert and notification 46 is recorded inthe notification store 122.

The alert processor 118 may query and extract information from therelationship store 114 via connection 218 using query element 258. Thealert processor 118 may query and extract information from the modelstore 106 via connection 180 using query element 258.

A recipient address store 266 is used by the constructor 124 inconjunction with a notification message rule-base 264 to generatenotification messages. The constructor 124 may use information from themodel store 106 or the relationship store 114 to construct thenotification content. The notification is sent via connection 128 to amessage broadcaster and transmission medium 270. The live informationwith collector 126 is sent to a live object broadcaster 268 which maygenerate or simply forward instructions for a graphical display of theinformation. The broadcaster 268 in turn presents the information to thegraphical user interface 130 of a browser. The message medium 134 may befor example e-mail 272, short message service (SMS) 274, fax service 276or voice mail service 278.

The processing system 101 is typically implemented in the form of one ormore computers or CPUs controlled by one or more computer programs,which comprise instructions, which when executed, control one or moreprocessors of the computers to operate as the processing system 101and/or to perform the method 10. The computer program will typically bestored in non-volatile storage and loaded into working memory. Thenon-volatile storage may be a hard disk drive, CD and DVD, flash driveetc. Working memory may be for example, random access memory (RAM).Alternatively the processors described above may be discrete physical orlogical processing units.

The processors 104, 112, 120, 129 may be in the form of virtualprocesses running on the system or discrete processing units allocatedto the particular task. The information stored in the model store 106,relationship store 114, notification store 122 and the variousrule-bases 156, 176, 168, 200, 220, 212, 250, 264 & 266 may beimplemented as one or more volatile or non volatile storage devices.

The system 101 can be implemented in a modular manner. For example, thesystem may comprise an object creator which triggers creation of anobject when input data meets one or more object creation criteria,wherein the objects created are at least two models representative ofreal-world things, at least one relationship between the models and analert object. A processor module may by used for each of the createdobjects. Each processor module is configured to receive data, processthe data including applying criteria to the received data, and store theprocessed data.

For the model objects, the received data are the measurement data items14, the criteria is one or more rules that reflect that the measurementdata is relevant to a characteristic of the real-world thing representedby the model and the stored data is one or more characteristics of themodel based on the measurement data.

For relationship objects, the received data are the modelcharacteristics, the criteria is one or more rules that reflect that thereal-world thing of one model has an influence over, relevance to or isrelated to the real-world thing represented by another model and thestored data is relationship properties based on the relevant modelcharacteristics.

For alert objects, the received data are the relationship properties,the criteria is one or more rules that reflect the relationship betweenthe modelled real world things is significant and the stored data is analert based on the relationship properties.

Referring to FIG. 6 an embodiment of an event driven architecture 300for implementing the processing system 101 is shown. The architecturecomprises an event processor 302, an event manager 306 and a reportmanager 308. The architecture 300 also has utilities 304 and an externalsystem 310.

The architecture 300 is typically implemented in an event driven mannerby using the event processor 302 to perform operations when an eventoccurs and by using the event manager 306 to route events. The eventprocessor 302 is arranged to implement modules to perform variousoperations including the operations of the model processor, relationshipprocessor and the alert generating processor. The event manager 306passes event messages to the relevant module in the event processor 302.

In an embodiment the architecture 300 implements the event processor302, event manager 306 and report manager 308 engine along with theutilities 304. The architecture 300 requires the processor modules,which may be in the form of plug-ins into the engine, to be developedaccording to the needs of the application to which the system 101 isbeing deployed. The deployment may also involve the one or more externalsystems 310. Some of the processor modules are custom built to provide aspecific implementation for the deployment, according to the real-timethings being monitored and the respective rules for generation ofmodels, relationships, alerts and notifications. That is some of theprocessor modules perform as a model processor, a relationship processorand an alert generating processor.

Utilities 304 are used to construct the customised modules. Theutilities 304 may comprise a state machine builder 336 and possibly aprocessor module Software Development Kit 338. The external system 310may include the data sources, transmission media 340 to and from theevent processor 302, and the live environment 130 and message medium134.

Each customised processor module may be implemented as a plug-in. Theplug-ins are developed as a separate class library which can be insertedinto a module repository of the event processor 302. The event processor302 will instantiate the plug-ins as necessary. Data contracts may beestablished between modules and the event manager 306 so that the eventmanager 306 is notified of an event. For example a module that producesX will broadcast that it can make X available and another module thatneeds X will let the first module know to send it X. Further an eventplug-in section of the event processor 302 is used so that the eventprocessor knows which plug-ins to load.

The state machine builder 336 assists in generation of a custom stateclass, a custom state machine class, tables and stored procedures neededto store the state machine's current state and state history. Togenerate the state machine class the user enters the possible states ofthe state machine, and custom fields needed to run the state machine.Database tables are then created. The state machine also assists byrecording definitions of the rules for transitions in the state machinemodel.

Event processor 302 comprises helper modules 312. Event processor 302also accepts and hosts the custom built modules 314 and handles deliveryof events to the modules 314. Events generated by the modules 312 or 314are provided to the event manager 306, which routes events back to theappropriate one of the other modules 312 or 314.

The helper modules 312 comprise one or more data acquisition modules 316and an event logger 318. The data acquisition module 316 may beconfigured to operate as source gateways 154, or may be configured tooperate as a precursor to the source gateways 154 by buffering inputfrom the data sources 100. In one embodiment the event logger 318listens for and records events in a database.

Customised modules 314 comprise an events API module 320, a helper Webservices module 322, customised state machines 326 and helper classes324. The modules are a class implemented for the particular application,and can directly access classes of the helper module 312. Events APImodule 320 provides functions that can be used with the other customisedmodules 314 to raise or capture events. The helper classes 324 areclasses that can be used by the custom modules 314 and are alsoavailable to the external systems 310. Helper classes 324 comprise ageography module 330, which is a generic geo-relational spatial featuremanagement class; an alert manager class 332, which provides genericalert condition evaluation and event raising; and a notification class334, which provides generic methods of delivering messages externally.The alert manager class 332 can operate as the alert processor 120 andthe notification class can operate as the notification messageconstructor 124.

The helper web services module 322 comprises an alert manager 328 whichis a template for configuring evaluation of alert conditions for modulesimplementing the alert manager helper class 332. The customised statemachine 326 is for example a class implemented for the solution based ona state machine class. Template state machine classes and associateddatabase containers are created using the state machine builder 336 at atime of devising the deployment implementation.

The report manager 308 provides methods of configuring and deliveringreports. The state machine builder 336 is a tool for creation of classesand database structure of the customised state machines 326. The moduleSDK 338 assists in developing the events API module 320 and othercustomised modules 314 according to the deployment implementationdesired.

The external system 310 accesses the utilities 304 by link 344 todefined state machines 326 and other modules 314. When the architectureis deployed the state machines and customised modules are “plugged into”the event processor 302 at 342.

Event manager 306 receives event messages by communication 346 generatedin the event processor 302 and routes these event messages to theappropriate destination module by communication 346. The report manager308 generates reports as desired from the event messages generated inthe event processor 302 and returns them over communication 348.

Referring to FIG. 7, the architecture of FIG. 6 is used in an exampleapplication 400 for monitoring a construction site. In this applicationit is desired to monitor a construction site to determine the locationand activities of vehicles within the construction site. The solutionarchitecture 400 comprises the engine 402 of FIG. 6 (including the eventprocessor 302 and event manager 306), the report manager 308 of FIG. 6,an Admin Web services component 404, a SQL Server 406, a solutionapplication server database 408, an events database 410 for the engine402 to store events in, a solution Admin website 412, a solution 3D Webclient 414, and a models definition 416 (rules by which vehicle modelsare generated updated and maintained).

Within the engine 402 some of the customised modules 314 are implementedas model modules which create and update models of the vehicles in theconstruction site according to the definitions 416. The model moduleswill establish a one or more state machines 326 for tracking the stateof each vehicle being modelled. The model modules may be regarded asoperating as the model processor 104 described above, with one of thecharacteristics of each model being its current state, which ismaintained by the respective state machine 326.

A sensor gateway module 424 is created to model a gate to theconstruction site. Further one of the customised modules 314 may model arelationship each of the vehicle models has with the gate model asdescribed further below. Such a module may be regarded as operating asthe relationship processor 112 as described above.

The alert manager 328 of the alert manager service module 322 may beconfigured to create an alert when a certain type of relationship iscreated between a vehicle (model) and the gate (model). In other words,the alert may be triggered when the relationship is in a certain state.This may indicate that the vehicle has passed through the gate. When thealert is created by the alert manager 328, a notification that thevehicle has passed through the gateway may be sent. The alerts arestored in the database 408 by communication 432. The database alsocontains rule-bases 430 related to generation and updating of models,relationships, alerts and notifications.

The alerts created by creation of the module, changes in status of amodel, creation of the relationship, changes to a relationship andgeneration of the alert are stored events database 410 by the eventslogger module 426.

When one of the models or relationships is desired to be fed into thelive environment, the live environment module 420 provides acommunication 438 of information to the solution 3D Web client 414. Aperson may wish to make a query on current state of a model. The queryis received and acted on by model query module 422, which provides aresponse to the solution 3D Web client 414.

The SQL Server 406 can access the database 408 by communication 450. TheSQL Server 406 comprises a custom delivery module 428 which cancommunicate 448 with the report manager 308 for producing customisedreports by email message 452 to an external destination. The reportmanager 308 communicates 442 with a solution Admin Web services module404 to configure the report manager 308. The Web services module 404 isaccessed by a solution Admin website 412. The solution Admin Webservices module 404 also communicates 446 with the solution 3D Webclient module 414.

FIG. 8 shows the modules within the construction site monitoringimplementation of the engine 402 in more detail. The modules comprisegate incident module 510, a Haul Truck module 512, a Water Truck module514, time on site module 516, proprietary GPS and telemetry modules 518and 520 (one for a LPOD GPS and one for a Minor Planet GPS). Othermodules comprise the live environment module 420, the model query module422, the alert manager module 322 and the event logger module 426, whichhave been described above.

Gate incident module 510 comprises a state machine 522, which trackswhether or not an authorised exit of the gate occurred, and anotherstate machine 526, which tracks whether there is an authorised entrythrough the gate. The gate incident module 510 follows the relationshipsbetween the vehicle models and the gate model. If a vehicle goes fromone side of a gate to another (as determined by a GPS data stream fromthe respective vehicle) the vehicle is regarded as passing through thegate. A rule-base may specify that if the vehicle passes through thegate at a certain time it is unauthorised. During other times thevehicle may be authorised to pass through the gate. The state of therelationship in the respective state machine is updated accordingly.

The haul truck module 512 comprises a state machine 534 for the haultruck, a state machine 538 for a load station and a state machine 542for a dump station. The haul truck module 512 follows the relationshipsbetween a haul truck vehicle model and its position relative to a loadsite and a dump site (as determined by a GPS data stream from the haultruck) and the time at the respective location. A rule-base may specifythat if the vehicle is stationary at the load site for a certain amountof time it is loading and when it then moves again it is loaded. Therule-base may also specify that if the vehicle is stationary at the dumpsite for a certain amount of time it is unloading and when it then movesagain it is unloaded. The state of the relationship in the respectivestate machine is updated accordingly.

The water truck module 514 comprises a state machine 546 for a watertruck and a state machine 550 tracking a state of a filling station. Thewater truck module 512 follows the relationships between a water truckvehicle model and its position relative to a water filling station (asdetermined by a GPS data stream from the water truck) and the time atthe water filling station. A rule-base may specify that if the vehicleis stationary at the water filling station for a certain amount of timeit is filling with water and when it then moves again it has finishedfilling. The state of the relationship in the respective state machineis updated accordingly.

A time on-site module 516 comprises a state machine 530 which trackstime on site of every vehicle as a relationship between the site areaand the vehicles. If there is a change in the relationship an event isgenerated, which will cause an alert, which will in turn generate anotification which may be sent to the database 408. A report on timespent on-site for each vehicle can be generated by report manager 308.

The model module 422 comprises a model playback service 554, a modeldashboard service 556 and an alert service 558. The model module 422 canaccess the database 408. The model playback service 554 allows therecorded changes to the models to be played back to a user. Thedashboard service allows the recorded measurement data to be played backin a dashboard display to a user.

FIG. 9 shows a state diagram 1400 implemented by a haul truck statemachine. The state machine has the following states: off 1404, idle1416, travelling full 1420, queuing dump 1432, dumping 1428, travellingempty 1442, queuing loader 1452, and loading 1462. All states except theoff state 1404 are regarded as operating states 1406. The state machinestarts at 1402 and transitions to the off state 1404. When the haultruck ignition is turned on, it transitions 1408 to a temporary historystate 1410. The history state will reinstate any prior state that thehaul truck was at before the ignition was turned off. If there is nohistory, then it transitions 1412 to the idle state 1414. From the idlestate 1414 if the truck remains idle, the state transitions 1416 back tothe idle state 1414. If the truck commences moving and it is full, ittransitions 1418 to the travelling full state 1420. While the truckremains full and is travelling, it transitions 1424 back to thetravelling full state 1420. The truck remains stationary in theproximity to the dumping station it transitions 1430 to the queuingstate 1432. When it remains in the queue it transitions 1434 back to thequeuing state 1432. When the truck reaches the dumping station, ittransitions 1436 to the dumping state 1428. Alternatively, if the truckarrives at the dumping station without queuing it transitions 1426 fromthe travelling full state 1420 to the dumping state 1428. While thetruck is dumping, it transitions 1438 back to the dumping state 1428.When the truck moves away from the dumping site, it transitions 1440 tothe travelling empty state 1442. While the truck continues to move, ittransitions 1444 back to the travelling empty state 1442. If the truckstops, it transitions 1446 to the idle state 1414. If the truckrecommences movement and is empty, it transitions 1448 to the travellingempty state 1442. If the truck is in the proximity of the loadingstation, but does not arrive at loading station, it transitions 1450 tothe queuing loader state 1452. While the truck remains there, ittransitions 1454 back to the queuing loader state 1452. When the truckarrives at the loading station, it transitions 1458 to the loading state1462. Alternatively, if the truck, having travelled empty, simplyarrives at the loading station it transitions 1460 to the loading state1462. While the truck remains at the loading station it transitions 1464to loading state 1462. When the truck commences movement away from theloading station, the state transitions 1466 to the travelling full state1420. At any stage, if the ignition is turned off, the state transitions1468 to the off state 1404. Furthermore, if any stage update data is notreceived within a certain time, the state transitions 1470 to the offstate 1404.

FIG. 10 shows a state diagram 1500 implemented by a water truck statemachine. The state machine has the following states: off 1504, idle1516, watering 1522, queue 1530, filling 1538, and travelling 1546. Allof the states except the off state 1104 are regarded as operating states1510. The state machine starts at 1502 and transitions to the off state1504. When the truck ignition is turned on, the state transitions 1508to an interim history state 1512. The state then returns to its previousstate before it was turned off, or if there was no previous state, ittransitions 1514 to the idle state 1516. While the truck remainsstationary it transitions 1518 back to the idle state 1516. From theidle state 1516, when the truck has water and is releasing water, ittransitions 1520 to the watering state 1522. While the truck remainswatering, it transitions 1524 back to the watering state 1522. When thetruck is in the proximity of the watering station, but not at thewatering station and is stationary, it transitions 1528 to the queuedstate 1530. While it remains there it transitions 1532 to the queuedstate 1530. When it reaches the filling station it transitions 1534 tothe filling state 1530. From watering 1522 if the truck arrives at thefilling station it transitions 1536 to the filling state 1538. While thetruck remains at the filling station, it transitions 1542 back to thefilling state 1538. If the truck leaves the filling station andcommences watering it transitions 1540 to the watering state 1522. Whenthe truck leaves the filling station, and does not commence watering, ittransitions 1544 to the travelling state 1546. If it keeps travellingwithout watering, the state transitions back to the travelling state1546. If from travelling 1546 the truck enters the proximity of thefilling station without actually being filled, it transitions 1550 tothe queued state 1530. If the truck, having been travelling 1546,commences watering it transitions 1552 to the watering state 1544. Ifthe truck, having been watering 1422, continues travelling withoutwatering, it transitions 1554 to the travelling state 1546. If havingbeen travelling 1546, the truck stops movement, it transitions 1558 tothe idle state 1516. If having been idle, the truck begins travellingwithout watering, it transitions 1556 to the travelling state 1546. Ifat any time the ignition is turned off, the state transitions 1560 tothe off state 1504. If at any time new data does not arrive within aspecified time period, the state transitions 1562 to the off state 1504.

FIG. 11 shows a screen shot of a graphical user interface (GUI) 1600 ofa live reporting environment in which a construction site is depicted.The GUI 1600 shows a loading area 1602, a dump site 1604 and a roadway1614. Also shown is a first truck 1602 and a details overlay box 1616which displays information about the first truck 1606 including itsstatus. The status of the first truck 1602 is Travelling Empty. A secondtruck 1610 is shown along with a details overlay box 1612 which displaysinformation about the second truck 1610 including its status. The statusof the second truck 1610 is Loading. Further, a third vehicle 1608 isshown along with a details overlay box 1618 which displays informationabout the third vehicle 1608 including its status. In this case thethird truck 1608 has exited the construction site unauthorised. Thestatus of the third truck 1608 is shown as Stolen. The positions of thetrucks 1606, 1608 and 1610 can be updated as new measurement data oftheir locations arrives.

Referring to FIG. 12, an example application 600 of the architecture ofFIG. 6 is used as an asset monitoring system. In this application assetsare monitored against threats. The solution architecture 600 comprisesthe engine 402 of FIG. 6 (including the event processor 302 and eventmanager 306), a database 608, a message server 652, a message receiver654, a presentation framework 656, a live server 658, a graphical userinterface 660, a presentation Admin website 662 and external datasources 664.

The engine 402 contains the custom modules 314 which are describedfurther in relation to the FIG. 13 further below. The engine 402accesses and provides information to the database 608 by communication632. The database 608 comprises rule-bases 630. The engine 602 generatesnotification messages 690 which are sent to the message server 652.Message server 652 functions as the broadcaster and transmitter 270. Itsends notifications over link 694 to the appropriate message receiver656, which may be for example e-mail application 272, a short messageservice receiver 274 or voicemail receiver 278.

Engine 402 sends live environment information 692 to live server 658,which then provides information to the graphical user interface client660. The graphical user interface client 660 is in this example is aSilverlight client, but it may be a Flash client or some other browserimplementation.

Presentation framework 656 comprises a map server 666, a project server668, an administration component 670, a map rendering server 672 and anauthentication server 674. The authentication server 674 authenticatesaccess to the external data sources 664. The administration component670 allows for control of the presentation framework 656 and storesparameters in the database 608. The administration component 670 isaccessed from presentation Admin website 662. Map server 666 includesload balancing 676. The map server 666 and map rendering server 672generate one or more maps for the live server 658 to provide to the GUIclient 660 to display to a user. The project server 668 managespredefined projects which are structured framework for graphicallypresenting and manipulating the resulting engine information.

FIG. 13 shows the modules within the asset threat monitoring systemimplementation of engine 402 in more detail. The modules are againimplemented as plug-ins and comprise the following: data gateway modules704, model processing models 706, composite model modules 708, virtualmodel models 710, threat relationship modules 712, message constructionmodule 716, live model service module 718 and events logger module 720.

The data gateway modules 704 operate as the gateways 154 to formatincoming data into a standard format. There is one module 704 for eachdata source. The model processing modules 706 operate as the modelprocessor 104. Each module 706 generates a model of an asset beingmonitored. The composite model modules 708 generate modules which arecomposite in nature, and based on two or more data sources. For example,an asset being modelled might be for example a power-line. A power-linemodel is constructed using one of the models 706. A bushf ire (wildfire)might also be modelled based on a combination of measurement data. Asatellite hotspot model may be created to receive satellite data and tomodel “hotspots”. However a hotspot is not necessarily regarded as abushfire. Bushf ire warnings may be generated by a firefighting servicemay also be available. The bushfire model may require measurement datain the form of the hotspot data and the bushf ire warning.

The virtual model module 710 creates and updates models of things thatare only indirectly related to the real-life thing or are onlyindirectly related to the real-life thing. For example the bushfiremight be modelled based on the combination of the hotspot model and thebushfire warning. In this case the model is based in part on anothermodel and not directly on measured information.

The threat relationship modules 712 operate as the relationshipprocessor 112 and analyses relationships between the models to createrelationship representations and properties of the relationships. Thoserelationships that generate alerts create events that go to thenotification analysis modules 714, which operate as the alert processor120. Those alerts that require notification use the message constructionmodule 716 to generate a notification. Thus the message constructionmodule 716 operates as the notification message constructor 124. Thelive model service module 718 generates the output to the liveenvironment. Each of the events created by the modules is logged by theevents logger module 720. These are stored in the events database 610.

An example list of real-life things that are modelled by this exampleare:

-   -   Satellite Derived Fires and associated swaths    -   Agency Reported Hazards    -   Fixed Assets    -   Administrative Areas and buildings    -   Mobile Assets    -   Weather Warnings    -   Lightning Strikes    -   Waves and Tidal Surges    -   Fires    -   Earthquakes    -   Floods    -   Weather Radars    -   Weather Observations    -   Cyclone Warning Areas    -   Cyclone Predicted Paths    -   Cyclone Tracks    -   Weather Forecast    -   Weather Model    -   User Input

FIG. 14 shows a state diagram 800 implemented by a threat relationshipstate machine. The state machine has the following states: active threat804, acknowledged threat 808, ignored threat 812 and inactive threat822. A relationship may be created when a new fire model event triggersa relationship evaluation with a power-line model. The power-line ispotentially threatened target. If the new fire model sufficientlyproximate to the power-line model, then the relationship is created. Thecreation of the relationship starts the state machine. Each state alsohas a small depiction of what might be displayed to a user of the liveenvironment. State machine commences by transitioning 802 to the activethreat state 802. The creation of this relationship will result the userbeing notified. User may respond by acknowledging the threat. A new“user input [acknowledged threat]” model event triggers a transition 806to be acknowledged threat state 808. From the active threat state 804 orfrom the acknowledged threat state 808, a new “user input [ignorethreat]” model event triggers and transition 814 or 810, respectively,to the ignored threat state 812. From the ignored threat state 812 a“user input [acknowledged threat]” model event triggers a transition 816to the acknowledged threat state 808. If an input is not received withina defined time then the present state is decayed, such that from theactive state 804 there is a transition 828, from the acknowledged threatstate 808 there is a transition 826, and from the ignored threat state812 is a transition 822, to the inactive threat state 822.Alternatively, if the fire model is updated so as to be deleted, thischanges the relationship such that if the current state is the activethreat state 804 there is a transition 830, or if the current state isthe acknowledged threat state 808 there is a transition 824, or if thecurrent state is the ignored threat state 812 there is a transition 818,to the inactive threat state 822.

FIG. 15 shows a screenshot of a live environment GUI in which a map 900is shown. On the map is a power-line 902 between the cities of Melbourneand Albury. Also shown is an area marked 904 which is annotated 906 asbeing a bushfire with a time and date. The bushfire 904 is proximate aportion of the power-line 902. This will trigger generation ofrelationship between the power-line 902 and the bushfire 904.

FIG. 16 shows a screenshot of live environment GUI, in which a map 950is shown. On the map is a sub-sea drilling rig “Crux” 952. A lowpressure cell is shown degenerating into a category 2 cyclone marked as970. The movement of the cyclone is tracked as it translates across themap to a position where is a category 1 cyclone, marked 972. Theproximity of the cyclone to rig 952 triggers a relationship andsubsequent notification with a warning to evacuate personnel on the rig952. A series evacuation routes 954, 956, 958, 960, 962, 964, 966 areplotted within the range of an evacuation helicopter at which there aresuitable landing sites. Some plots cross the path of the cyclone and aretherefore ruled out. Plot 960 may be a sufficiently ahead of the cyclonewhen it is at position 972, however preparation time and travel time mayrule this route out as well. Furthermore, predicted cyclone positions974 and 976, may also rule out route 960. An area of affect of thecyclone is marked as 980. Travel within this area by helicopter wouldnot be permitted.

Referring to FIG. 17, there is shown in further embodiment of a system1000 for generating alerts. The system 1000 comprises a timeconfiguration input 1002, a hazard data input service 1004, astakeholder contact database service 1006, a target asset service 1008,communication medium 1010, an application server 1012, administrationservice 1014, communication medium 1016, a notifier 1018, atelecommunication service 1020, mobile device 1022, email transfermedium 1024, email receiver 1026, stakeholder 1028 and Web servicebrowser 1030.

The time configuration input 1002 configures the updating of data inputand/or alert checking. The input data service 1004 receives measurementdata of hazards to assets. Stakeholder contact database service 1006contains contact details for stakeholders 1028. This may be for exampleinformation to enable contact of the stakeholder by telecommunicationservice 1020 or e-mail 1024. The target asset service 1008 defines theposition of assets to be monitored against hazards. Communication medium1010 receives information from systems 1002, 1004, 1006 and 1008 andsends these to the application server 1012.

The application server 1012 monitors for proximity between the measuredlocation data relating to hazards and the location of assets fromsystems 1002 and 1004, respectively. A hazardous relationship isregarded to exist when the proximity of the hazard and asset are tooclose. This generates an alert, which is sent across communicationmedium 1016 to server 1018. Application server 1012 may be administeredvia administration service 1014.

The alert triggers notification message server 1018 to generate anotification based on the contact details provided by server 1006. Forexample, the message is send to mobile device 1022 overtelecommunication service and/or and email is sent to e-mail receiver1026 via email transfer medium 1024. This message relating to the hazardthreatening the asset can then be drawn attention of the stakeholder1028, who can take action. The stakeholder can also monitor the hazardover the secure browser access 1030, which maps the location of theassets and hazards to provide visual indication to the stakeholder ofthe relationship between the hazard and asset.

Filtering may be applied to the alerts, such that alerts are onlymaintained in predetermined conditions. A notification is only sent whenthe alert is maintained. The input 1002 can configure the period inwhich processing of the measurement data occurs. The input 1002 can alsoconfigure the period between processing the measurement data.

An example of asset monitoring 1100 from fire threats is described belowin relation to FIG. 18. The asset monitoring 1100 may be implementedusing the application 600, or by other another system described above.The system has an input or inputs for receiving external data 1102, anumber of processes 1104, a storage or memory for storing objects data1106, a presentation process 1108 for presenting notifications to endusers 1110. The objects data 1106 is information defining thecharacteristics of objects. The objects are at least models,relationships or alerts, as described above.

The objects broadcast information detailing their changes in state asEvents. These Events are of three main types and are classified asfollows:

Event Type Description New Object This Event is broadcast by an Objectwhen it has been newly created. Updated Object This Event is broadcastby an Object when one of its Characteristics changes. Archived ObjectThis Event is broadcast by an Object when it has been deleted.

The external data 1102 comprises agency fire notices 1120, satellitederived hotspots 1122, and asset descriptions 1124. The agency firenotices 1120 are obtained from a database maintained by or constructedfrom information provided by emergency service agencies (for example afire fighting department). This data comprises descriptions of fires ofinterest. Each fire description comprises a time identified, a name (orother identifier), a status of the fire (for example out-of-control,under-control, contained) and a geographic area or extent. This data mayarrive with a frequency of about once per 5 minutes to once per 6 hours.

The satellite derived hotspots 1122 comprise regions indicating a firein or derived from an imaged captured by a satellite. The data is in theform of latitude and longitude, and confidence. The data is obtainedfrom various ground stations after each satellite overpass. This datamay be provided at about 3-6 hour intervals.

The asset descriptions 1126 comprise data describing assets of interest,in this case powerlines. The descriptions comprise a name and uniqueidentifier of the asset, a spatial geometry of the asset and location ofthe asset. This information may be provided by the owner of the assetabout every 3-12 months.

The processes 1104 comprise a model processor 1130, a relationshipprocessor 1132, an alert processor 1134, a notification processor(notifier) 1136 and a messaging services processor 1138. Theseprocessors create update and archive the objects by maintaining theobject data 1106 according the new Events.

The model processor 1130 comprises a number of sub-processors, namely apower asset processor 1140, a fire processor 1142, and an agency fireprocessor 1144. Each of the model sub-processors processes the relevantexternal data 1102 as is arrives, after a period of time or when apredefined signal is received. The model sub-processors add, update orarchive models 1150 based on criteria, namely evaluation of respectivemodel rules, and assign or update model characteristics.

-   Model Characteristics:-   Model Type Identifier-   Model Identifier-   Geometry in Geographic Coordinate System-   Valid Time Period-   Current State-   Collection of properties

The power asset processor 1140 creates or updates a powerline assetmodel 1152 for each asset in response to receiving the power assetdescriptions 1124.

Power Asset Model Template

Characteristic Description Identifier Unique identifier for the PowerAsset (as provided by the asset owner) Geo graphic Area/ Point, Line orPolygon representing the shape and Geometry location of the Power AssetValid Time Period From last update to now Current State Active orInactive Property1 Owner: The name of the Asset Owner Property2 Type:The Type of Power Asset (i.e. Overhead Power Line, Underground PowerLine, Electricity Sub Station) Property3 Voltage: The voltage thatElectric Power is being transmitted through the Power Asset.Notification List of Notification Profile Identifier-Timestamp Timestamppairs representing the last time a notification was sent for eachNotification Profile for this Model.

The agency fire processor 1144 creates and updates agency fire models1156 based on the agency fire notices1120. When a new agency fire notice1120 is received (fetched or an update sent) for each identified fire,if an agency fire model having the same identifier does not exist then anew agency fire model is created and assigned characteristics accordingto the agency fire notice (eg the location). When a model 1156 alreadyexists the characteristics are updated. When a fire is no longerdetailed within an agency fire notice 1120 the agency fire model isarchived.

Agency Fire Model Template

Characteristic Description Type Identifier 001 Identifier Name GeometryPolygon of fire boundary Valid Time Period From creation time until nowCurrent State Fire Status (controlled, going, not controlled, etc..)Property1 Source: Agency Name Property2 Type: Fire type (i.e. grassfire)

Model Example

Characteristic Value Identifier Southern Hills 23 Geometry Polygon offire boundary Valid Time Period 2009-09-21 12:01 to 2009-09-22 8:00Current State controlled Source GeoMac Type Grassfire

In one example, the derived fire processor 1142 creates and updates aderived fire model 1154 based on the satellite fire models 1154 based onhotspot data and agency fire models 1156 according to a set of rules.

In this example the derived fire models are created based on thecharacteristics of other models, that is, a satellite model and anagency fire model. Another way of producing derived fire models is toprocess all the satellite hotspot data 1122 and the agency fire notices1120 to produce composite fire models. A further way to produce aderived fire model is to determined relationships between the satellitemodels and the agency fire models based on proximity and or overlappinggeographic location and from those relationships to create the derivedfire models. Which of these techniques is used may depend on thespecific objectives of the implementation.

Derived Fire Model Template

Characteristic Description Identifier Name (i.e. Southern Hills 23) fornamed fires Geographic area Aggregated polygon of fire boundary ValidTime Period From original source creation time until now Current StateFire Status (controlled, going, not controlled, etc..) Property1Sources: Agency Names, Satellite etc Property2 Type: Fire type (i.e.grassfire) Property3 Confidence: Likelihood of being a fire Property4Remarks: any comment from sources

The relationship processor 1132 adds, updates or deletes relationships1162 in response to model events (ie creation, update or archive of amodel 1150). The relationship processor 1132 identifies models 1150 thatare in a relationship based on relationship criteria and calculatesrelationship properties.

In this implementation the relationship criteria are configured tomonitor for threats to the power assets from fires. Thus therelationship processor 1132 is configured to operate as a fire-assetanalyser 1160. The fire-asset analyser 1160 is configured to assess ifrelationship criteria are met when a new derived fire model is createdand if so to create a new fire-asset relationship 1164 between therespective derived fire model 1154 or agency fire model 1156 and therelevant power asset model 1152 and calculate the fire-assetrelationship's properties. The derived fire model/agency fire model1154/1156 and the power asset model 1152 are regarded as members of therelationship 1164.

When a fire model 1154 or 1156 is updated:

-   -   If the fire model is a member of an existing fire-asset        relationship then        -   the relationship criteria is assessed and            -   if met then the fire-asset relationship is updated            -   if not met then the fire-asset relationship is deleted    -   If the fire model is not a member of an existing fire-asset        relationship then        -   -   the relationship criteria is assessed and if met then a                new fire-asset relationship is created and properties                are calculated

For archive derived fire model Events: if the derived fire model is amember of an existing fire-asset relationship then the relationship isdeleted.

Relationship General Characteristics:

-   Unique Relationship Type Identifier-   Unique Relationship Identifier-   Relationship Criteria (identifies members)-   Model Members (Relationship must have a Member cardinality of at    least 2)-   Relationship Properties (defined by the Member Relationships. i.e.    closest members, min distance between members of different types,    new derivative Models)

Example Relationship Properties Profile

Relation Type Identifier: 001

Criteria: Power Asset Models (A,B,C) of type X within 5000m of a DerivedFire Model (1) form the relationships 1ABC

Members: 1 Derived Fire Model, 1 or more Power Asset Model

Properties: Active=TRUE, Calculated minimum distance between the DerivedFire Model member and a Power Asset Model member

The alert analysis processor 1134 assesses an alert criteria in respondto a relationship event (when a new relationship is created, when arelationship is updated or when a relationship is deleted). The alertanalysis processor 1134 generates an alert 1172 and calculates alertproperties if the alert condition is met. In this implementation thealert analysis processor 1134 is configured to operate as a fire-assetalert analyser 1170. The fire-asset alert analyser 1170 is configured toconsider fire-asset relationship events.

For a new fire-asset relationship event, the fire-asset alert criteriais assessed and if met then a new fire-asset alert 1174 is created andproperties are calculated.

For an update fire-asset relationship event:

-   -   If a fire-asset relationship is the source of an existing        fire-asset alert then        -   the alert criteria is assessed and            -   if met then the fire-asset alert is updated            -   if not met then the fire-asset alert is deleted    -   If a fire-asset relationship is not the source of an existing        fire-asset alert then        -   the fire-asset alert criteria is assessed and if met then a            new fire-asset alert is created and properties are            calculated.

For archive fire-asset relationship events:

-   -   If the fire-asset relationship is the source of an existing        fire-asset alert then the alert is deleted

Alert General Characteristics:

-   Unique Alert Type Identifier-   Unique Alert Identifier-   Source Relationship-   Alert Rule Conditions Met-   Alert Properties (derived or calculated from Source Relationship and    its Members)

Alert Properties Profile

Relation Type Identifier: 001

Source Relationship: Fire-Asset Relationship

Alert Rule Conditions: Relationship is active

Alert Properties:

-   Calculated minimum distance between the Derived Fire Model and a    Member Power Asset Model-   Derived fire model Member Identifier-   List of Power Asset Model Member Identifier

EXAMPLE

Alert Type Identifier: 0000021

Alert Identifier: 00009898

Minimum Distance: 421m

Fire: Southern Hill 23

Power Assets: CKY, SMS, SVA, MSA, MSV, RBW, MSN, BRT, TYN, KLV

The notification construction processor 1136, in response to alertevents (creation, update or deletion of an alert) identifies relevantnotification profiles, assesses notification criteria (i.e. Re-warnInterval), constructs a notification message content, updates model'snotification timestamps and generate notifications 1182.

In this implementation notifications are sent to a power asset's owner(relevant person(s) or warning/monitoring system) when a fire threatensan asset according to a specified profile. The notification constructionprocessor 1136 is configured to act as a fire-asset alert notificationconstructor 1180 such than in response to new fire-asset alert events:

-   -   For each notification profile having a source fire-asset alert        -   A new fire-asset notification 1184 or 1186 is created        -   For each unique power asset model (A) listed in fire-asset            alerts            -   The fire-asset notification criteria is assessed (such                as re-warn interval is less than the time since last                fire-asset notification for power asset model A)            -   A fire-asset notification message content is added            -   A notification timestamp list is updated for power asset                model (A)

The notification construction processor 1136 is configured such than inresponse to update fire alert events

-   -   For each notification profile having a source fire-asset alert        -   An update fire-asset notification 1188 or 1190 is created        -   For each unique power asset model (A) listed in fire-asset            alerts            -   The fire-asset notification criteria is assessed (such                as re-warn interval is less than the time since last                fire-asset notification for the power asset model A)            -   A fire-asset notification message content is added            -   A notification timestamp list is updated for power asset                model (A)

Notification General Characteristics:

-   Unique Notification Profile Identifier-   Unique Notification Identifier-   Time Sent-   Time Generated-   Delivery Type [SMS, eMail, Interactive]-   Message Content

New eMail Notification Profile:

Source Alert: Fire-Asset Alert

End User: User-1 (Asset Manager), User-2 (Rostered Network Controller)

Service Delivery type: eMail

Message Template: <Subject> <Message Content> <Footer>

Re-warn Interval: 10 minutes

Event Type: New

Update eMail Notification Profile:

Source Alert: Fire-Asset Alert

End User: User-1 (Asset Manager), User-2 (Rostered Network Controller)

Service Delivery type: eMail

Message Template: <Subject> <Message Content> <Footer>

Re-warn Interval: 10 minutes

Event Type: Update

Update Interactive Notification Profile:

Source Alert: Fire-Asset Alert

End User: User-1 (Asset Manager), User-2 (Rostered Network Controller)

Service Delivery type: Interactive

Message Template: <Subject> <Message Content> <Footer>

Re-warn Interval: 1 minutes

Event Type: Update

New Interactive Notification Profile:

Source Alert: Fire-Asset Alert

End User: User-1 (Asset Manager), User-2 (Rostered Network Controller)

Service Delivery type: Interactive

Message Template: <Subject> <Message Content> <Footer>

Re-warn Interval: 1 minutes

Event Type: Update

The messaging services processor 1138 is configured so that in responseto new notification events. A notification 1182 is allocated to amessage queue 1192 based on “Delivery Type” and delivery of messagesfrom message queue is managed. The message queue is configured such thatin response to new fire-asset notifications:

-   -   If Delivery Type=“SMS” then place the notification on the SMS        Delivery Queue    -   If Delivery Type=“eMail” then place the notification on the        eMail Delivery Queue    -   If Delivery Type=“Interactive” then broadcast the notification        for use by a Website—Pop-up Toaster 1196 of the presentation        processor 1108.

The SMS Queue management:

-   -   Takes the next notification from the front of the SMS Delivery        Queue    -   Delivers the notification message to the user's        SMSDeliveryAddress    -   Updates the SMS Delivery Queue

The eMail Queue management:

-   -   Takes the next notification from the front of the eMail Delivery        Queue    -   Delivers the notification message to the User's        eMailDeliveryAddress    -   Updates the eMail Delivery Queue

The SMS and eMail Delivery Queues send the notification 1182 to theuser's mobile telephone, or eMail address, respectively. In analternative, the notification 1182 is sent to a facsimile machine.

An example of asset monitoring 1200 from lightning threats is describedbelow in relation to FIG. 19. The asset monitoring 1200 may beimplemented using the application 600, or by other another systemdescribed above

The system has an input or inputs for receiving external data 1202, anumber of processes 1204, a storage or memory for storing objects data1206, a presentation process 1208 for presenting notifications to endusers 1210.

The external data 1202 comprises a lightning data stream 1220 and assetdescriptions 1222. The lightning data stream 1220 is provided by asource in a digital form in real time. The lightning data stream 1220comprises textual properties including time of strike, amplitude, typeand a spatial point (latitude, longitude) and a geographic location.

The asset descriptions 1222 comprise data describing assets of interest,in this case powerlines, microwave towers or other assets vulnerable toa lightning strike. The descriptions comprise a name and uniqueidentifier of the asset, a spatial geometry of the asset and location ofthe asset. This information may be provided by the owner of the assetabout every 3-12 months.

The processes 1204 comprise a model processor 1230, a relationshipprocessor 1232, an alert processor 1234, a notification processor 1236and a messaging services processor 1238.

The model processor 1230 comprises a number of sub-processors, namely apower asset processor 1240 and a lightning strike processor 1242. Eachof the model sub-processors processes the relevant external data 1202 asis arrives, after a period of time or when a predefined signal isreceived. The model sub-processors add, update or archive models 1250based on criteria, namely evaluation of respective model rules, andassign or update model characteristics.

The power asset processor 1240 creates or updates a power asset model1252 for each asset in response to receiving the power assetdescriptions 1222.

The lightning strike processor 1242 creates or updates a strike locationmodel 1254 for each lightning strike in response to receiving thelightning data stream 1220.

-   -   In response to new lightning data from the lightning data stream        1220:        -   Create a new Strike Location Model 1254 based on the            received Lightning Data.        -   Set the Model Expiry Time as 10 minutes after the model has            been created. (Once this is reached the model will be            deleted)    -   When the Strike Location Model Expiry Time is greater than or        equal to now, delete the Strike Location Model 1254.

Strike Location Model Template

Characteristic Description Type Identifier 004 Identifier Name GeometryPoint representing Strike Location Valid Time Period 10 Minutes fromcreation time Current State Strike Status (based on TTL) Property1 Type:(Cloud to Cloud, Cloud to Ground) Property2 Amplitude: Amplitude of themeasured Lightning Strike

Model Example

Characteristic Value Identifier Strike 3003 Geometry Point representingStrike Location Valid Time Period 2009-09-20 06:08 to 2009-09-20 06:18Current State 50% Type Cloud to Ground Amplitude 40 kA

A model for the location of a cloud to ground Lightning Strikeincorporates properties of the source and a point geometry and is ofinterest for a finite period defined by a decay rule.

Strike-Asset Alert Example:

Alert Type Identifier: 0000043

Alert Identifier: 00009987

Minimum Distance: 312m

Power Asset: CKY

Strike Locations: 212, 213, 217, 218, 220

The relationship processor 1232 adds, updates or deletes relationships1262 in response to model events based on relationship criteria andcalculates relationship properties.

In this implementation the relationship processor 1232 is configured tooperate as a strike-asset analyser 1260 such that the relationshipcriteria are configured to monitor for threats to the power assets fromlightning strikes.

-   -   In response to new Strike Location Model Events        -   Relationship Criteria is assessed and if met a new            Strike-Asset Relationship 1264 is created and properties are            calculated    -   For Delete Strike Location Model Events:        -   If the Strike Location Model 1254 is the only remaining            Strike Location Model member of an existing Strike-Asset            Relationship 1264 then the relationship is deleted

Example Relationship Profile

Relation Type Identifier: 001

Criteria: Power Asset Model (A) of type X within 5000m of Strikelocation Models (1,2,3) form the relationship (A123)

Members: 1 Power Asset Model, 1 or more Strike Location Models

Properties: Active=TRUE, Calculated minimum distance between the StrikeLocation Model member and a Power Asset Model member

The alert analysis processor 1234 assesses an alert criteria in responseto a relationship event and generates an alert 1264 and calculates alertproperties if the alert condition is met. In this implementation thealert analysis processor is configured to operate as a Strike-AssetAlert Analyser 1270 configured to consider strike-asset relationshipevents.

-   -   In response to new Strike-Asset Relationship Events        -   Strike-Asset Alert Criteria is assessed and if met new            Strike-Asset Alerts 1274 are created and properties are            calculated    -   In response to Update Strike-Asset Relationship Events:        -   If Strike-Asset Relationship 1264 is the Source of an            existing Strike-Asset Alert 1274            -   Alert Criteria is assessed and            -   if met then Strike-Asset Alerts are updated            -   if not met then Strike-Asset Alerts are deleted        -   If Strike-Asset Relationship 1264 is not the Source of an            existing Strike-Asset Alert 1274 then            -   Strike-Asset Alert Criteria is assessed and if met then                new Strike-Asset Alerts 1274 are created and properties                are calculated    -   For Delete Strike-Asset Relationship Events:        -   If Strike-Asset Relationship 1264 is the Source of an            existing Strike-Asset Alert 1274 then the Alert is deleted

Example Alert Profile

Relation Type Identifier: 010

Source Relationship: Strike-Asset Relationship

Alert Rule Conditions: Relationship is active Alert Properties:

-   Calculated minimum distance between the Member Power Asset Model and    a Member Strike Location Model-   Power Asset Model Member Identifier-   List of Strike Location Model Member Identifiers

The notification construction processor 1236, in response to alertevents identifies relevant notification profiles, assesses notificationcriteria, constructs notification message content, updates the model'snotification timestamps and generates notifications 1282. In thisimplementation notifications are sent to a power asset's owner when alightning strike may affect a power asset according to a specifiedprofile. The notification construction processor 1236 is configured suchthan in response to new strike-asset alert events.

The messaging services processor 1238 is configured so that in responseto new notification events a notification 1282 is allocated to a messagequeue 1290 and delivered to the user.

Modifications and variations as would be apparent to a skilled personare intended to fall with in the scope of the present invention.

1. In a processing system a method comprising: receiving measurementdata; processing the measurement data to create or update at least twomodels and one or more characteristics associated with each model basedon the measurement data, where each of the models is a representation ofa real-world thing; processing the characteristics associated with themodels to form one or more new relationships between the models when thecharacteristics are such that two or more of the models are regarded asbeing related according to one or more relationship criteria; andprocessing the relationships to generate one or more alerts when one ormore of the relationships meet one or more alert criteria.
 2. In aprocessing system a method comprising: receiving measurement data,wherein the measurement data is obtained by measuring at least tworeal-world things; processing the measurement data to create at leasttwo models, each model representing one of the measured at least tworeal world things; processing the measurement data to create one or morecharacteristics associated with each model based on the measurementdata, wherein the characteristics describe the respective real-worldthing and/or its behaviour as measured; receiving updated measurementdata, wherein the updated measurement data is obtained by a latermeasurement of the at least two real-world things; processing theupdated measurement data to update each of the at least two models andto update the one or more characteristics associated with each modelbased on the updated measurement data; providing one or morerelationship criteria for testing whether two models are to be regardedas related according to the type of thing that the real-world things arerepresenting; processing the characteristics associated with the modelsby testing whether the relationship criteria are met, and in the eventthat the relationship criteria are met forming one or more relationshipsbetween the models that meet the relationship criteria; processing thecharacteristics associated with the models to form characteristicsassociated with formed relationships between models; processing theupdated characteristics associated with the models to update thecharacteristics associated with the relationships; providing one or morealert criteria for testing whether a relationship between modelsrequires alerting; processing the characteristics associated with therelationships by testing whether the alert criteria are met, and in theevent that the alert criteria are met generating one or more alerts.processing the characteristics associated with the relationships bytesting whether the alert criteria are met, and in the event that thealert criteria are met generating one or more alerts.
 3. A methodaccording to claim 1, wherein one of the real-world things is an assetand one of the real-world things is an event or phenomenon.
 4. A methodaccording to claim 3, wherein the or each asset are fix in geographiclocation and the events or phenomenon are created when they potentiallyor actually pose a threat to the or each asset due to geographicalproximity to the one or more of the assets.
 5. A method according toclaim 1, wherein each event or phenomenon model has a delay state thatreduces the relevance of the model over time unless new measurement datais received that relates to the respective model.
 6. A method accordingto claim 1, wherein each relationship has a delay state that reduces therelevance of the relationship over time unless a change incharacteristics associated with the respective models between whichthere is the respective relationship is processed.
 7. A method accordingto claim 2, wherein one of the real-world things is an asset and one ofthe real-world things is an event or phenomenon.
 8. A method accordingto claim 7, wherein or each asset are fix in geographic location and theevents or phenomenon are created when they potentially or actually posea threat to the or each asset due to geographical proximity to the oneor more of the assets.
 9. A method according to claim 2, wherein eachevent or phenomenon model has a delay state that reduces the relevanceof the model over time unless new measurement data is received thatrelates to the respective model.
 10. A method according to claim 2,wherein each relationship has a delay state that reduces the relevanceof the relationship over time unless a change in characteristicsassociated with the respective models between which there is therespective relationship is processed.